Research Center Trustworthy Data Science and Security

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The Research Centre addresses the challenge of building trust in Artificial Intelligence, Machine Learning, and Cybersecurity. The focus is on trustworthy systems for safety-critical applications. A human-centred approach shapes the interdisciplinary research on trustworthy data analysis, explainable machine learning, and privacy-aware algorithms. The aim is to develop reliable systems and support people in understanding technology.

Website of the Research Center

Prof. Dr. Nicole Krämer, Director

"Like in a giant field experiment, people in their daily lives are increasingly confronted with ever evolving AI systems. RC Trust is committed to contribute to fundamental research demonstrating that interdisciplinary collaboration of machine learning, data science, cybersecurity and psychology is needed in order to improve current technology and help users to develop a degree of trust that matches the system's actual trustworthiness."

Research

The Centre for Trustworthy Data Science and Security envisions a unique interdisciplinary research approach that addresses the entire spectrum of challenges across all facets of trustworthy and privacy-aware technologies. Meaningful progress in these areas requires close collaboration across a variety of disciplines. Therefore, the Research Centre builds upon the strengths of the University Alliance Ruhr in the following fields.

Psychology and Social Sciences:

"We explore the (psychological) mechanisms of how humans interact with AI – focusing on how individuals understand the way that the system works and how they perceive, develop and maintain trust. Our work is empirically driven and encompasses qualitative and quantitative methods." Prof. Dr Nicole Krämer, University of Duisburg-Essen.

Data Science and Statistical Learning

"Our group aims to draw more conclusions from our data and better understand the processes and structures underlying data analytics. To accomplish this, we design methods and algorithms based on fundamental statistical concepts, including uncertainty quantification or causation." Prof. Dr. Markus Pauly, TU Dortmund University

Artificial Intelligence and Machine Learning

"Our research covers data mining, machine learning, scalable algorithms and interactive exploration of high dimensional data, complex graphs, time series, and data streams. The research lays the foundation for autonomous and trustworthy systems." Prof. Dr. Emmanuel Müller, TU Dortmund University

Collaborative Projects and Graduate Training

The Research Center builds on a strong and long-standing foundation of individual research projects, collaborative projects, and interdisciplinary graduate education. Seven ERC-funded projects, one cluster of excellence, two collaborative research centers, five interdisciplinary graduate schools, and one federal competence center in machine learning are a testament to the strength of research in this area: